BMA, our potential superheroes…pending

Connor Graham, Francis Marion University


Findings: At the beginning of this summer my mentors and I had specific objectives and questions we wanted to answer regarding the biogeography of benthic microalgae and of course like any experimental hypotheses, things change. Our main objective was to identify the community structure on five barrier islands on South Carolina’s coast and see if there were differences. If there were differences were they because of geographic distance or environmental factors?  As the summer progressed our questions changed slightly to look more at community biomass instead. Of course our questions link back to the larger picture of using these diatoms as bioindicators for environmental health.

Community structure is composed of two main components: biomass and DNA composition. Biomass is the mass of the organisms present in a given area. Even though we collected samples for DNA, we had an allotted time which only allowed for analyzation of the biomass samples which were chlorophyll a. So, now our main questions were: Are there differences in community biomass among islands? Are those differences due to geographic distance or environmental factors like water temperature, nutrients, wind, pressure and so many more.

Based on the results from the data we have, biomass does indeed differ among islands, geographic distance is not the reason, but instead a few environmental factors. Those significant environmental factors are located in the table below. Still taking in account that we have pending analysis for DNA composition, nutrients and grain size, our original questions could be supported quite differently.


The result of an ANOVA test which showed biomass differences among islands. The p-value was less than 0.0001.




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This p-value of 0.439 shows that Geographic distance is not correlated with community BMA biomass.

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These are the significant environmental factors that correlate with BMA biomass, with water temperature being the most significant with a p-value of 0.001.

However, if we do see that community structure is not affected by the differences in locations, then potentially there is no dispersal limitation on our microbes. Also, if community structure is also impacted by environmental like biomass, then we could potentially use this to measure bioindication by adding in a new factor.

As of now, we are not sure if diatoms can be used as bioindicators, and if they are the superheroes we need. However, we do know that more research is needed to find out and until then our great state awaits its savior.


A picture of me covered in mud at Hunting Island after a day of sampling. Photo: Max Cook


I would like to thank my mentors: Dr. Craig Plante and Kristina Hill-Spanik (CofC). Also, I would like to thank my lab partner Max Cook (CofC). This project is supported by the Fort Johnson REU Program, NSF DBI-1757899.